Mechanical engineer Scott Whalen is named the Department of Energy’s Innovator of the Year for turning the patented metal extrusion invention ShAPE™ into an industrially relevant extruded metal product juggernaut.

Chiral nanotubes facilitate the direction-specific diffusion of carbon dioxide to be faster than nitrogen gas.

A new report highlights a public workshop hosted by the National Academies Forum on Microbial Threats and features PNNL's Lauren Charles and the AI-Driven One Health Security program.

A research team from Pacific Northwest National Laboratory used machine reasoning to schedule scientific workflows while guaranteeing quality of service (QoS).

PNNL researchers highlighted advances in AI for scientific discovery at the AI+ Expo, showcasing generative AI, autonomous research workflows, and scalable AI systems supporting energy, security, and national competitiveness.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

Critical minerals could be sourced from industrial waste at scale thanks to an AI-guided separation workflow developed by researchers at PNNL.

At a geospatial intelligence conference, senior data scientist Adam Attarian participated in a panel discussing how national laboratories are delivering science, technology, and partnerships to enhance modeling, analysis, and innovation.

Graduate student researcher wins best poster awards from the American Ceramic Society.

PNNL researchers will deploy advanced AI systems to study how to best secure the future electric grid.

High-Velocity Joining is a new joining technology that could reduce energy use and cost for manufacturers.

PNNL’s Robert Rallo and Nathan Hodas speak to students about the future of AI.

A newly published custom collection of glass formulas for nuclear waste vitrification — developed and validated by PNNL over the past three years — was made possible in that timeframe with AI tools, including a PNNL machine learning model.

Scientists are optimizing microbes to harvest critical minerals and produce bioproducts using AI and autonomous lab equipment.

At the summit, PNNL engaged with partners and investors, highlighting seven projects that accelerate the deployment of new energy technologies.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

David Wunschel, a chemist and Laboratory Fellow, participated on a panel focused on how emerging technologies are transforming CBRN defense, detection, and response across military and government operations.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

PNNL cyber defenders are using the Laboratory’s own artificial intelligence research to recognize and address threats quickly.

Custom AI research assistant allows users to ask questions and get answers from hundreds of wildfire mitigation plans.